Classical incident-response frameworks fall short for AI incidents because they do not capture probabilistic failures and a new classification schema with separate playbooks for model-induced and externally-induced failure scenarios is required.
The U.S. Department of the Treasury sanctions a VPN provider for the first time for systematically supporting ransomware groups and other cybercriminals.
Without isolated, immutable and strictly controlled backups, 84.5 percent of attacked companies do not pay ransom and still recover, while paying companies fail 8–33 percent of the time and face additional insurance and sanctions risks.
Attackers are exploiting abandoned and compromised GitHub accounts to systematically reconnaissance company structures and in some cases exfiltrate private code repositories.
An in-memory RAT named GoodPersonRAT is being distributed through fake LetsVPN installer packages and requires immediate vigilance regarding the origin of VPN software.
While AI-powered attackers refine social engineering methods, CISOs lose management support for employee security and must meet conflicting stakeholder expectations.
AI agents automate complete attack chains without requiring zero-days, instead systematically exploiting known vulnerabilities and misconfigurations at machine speed.
Over 75 percent of European CISOs report that their executives underestimate cyber risks from employee errors, while AI-driven attacks increasingly exploit these vulnerabilities with precision.
